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Resume enhancer

Skill Sheshiyer/skill-clusters/skills/resume-enhancer

Rewrite and optimize resumes for target roles with stronger impact bullets and ATS keyword alignment. USE WHEN a task matches the Craft workspace workflow for resume-enhancer.From its SKILL.md

Install
npx -y skills add Sheshiyer/skill-clusters --skill resume-enhancer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.5 KB, 237 tokens by cl100k_base, as published. Nobody here has run it

Resume Enhancer

Use this skill when the user wants to improve a resume for specific roles, improve ATS fit, and increase interview conversion.

Trigger Conditions

  • User asks to improve or rewrite resume
  • User asks for ATS optimization
  • User wants role-specific resume tailoring

Required Inputs

  1. Existing resume text
  2. Target role(s) and job descriptions
  3. Key achievements and measurable outcomes
  4. Preferred geography/industry (optional)

Workflow

  1. Target extraction: identify keywords, required skills, and role expectations.
  2. Resume audit: assess clarity, relevance, and quantification.
  3. Rewrite: improve summary, experience bullets, and skills section.
  4. ATS optimization: map keywords naturally and remove weak phrasing.
  5. Final polish: consistency check for formatting and impact.

Output Format

  • Before/after improvement summary
  • Rewritten resume sections
  • ATS keyword match list
  • Top 5 additional edits user should make

Guardrails

  • Never invent companies, titles, or achievements.
  • Prefer quantified outcomes and concrete verbs.
  • Avoid stuffing keywords unnaturally.

What ships with it: 1 file

560 B alongside SKILL.md

Gives 0 of the 12 instructions most hr recruiting skills give in 237 tokens

Counted across 356 of the 357 authors here whose files we hold, read 2026-08-07

  • Quantify achievements with specific metricsin 14 of 356, across 6 files
  • Keep the resume under two pagesin 14 of 356, across 6 files
  • Request the full job description if not providedin 12 of 356, across 4 files
  • Extract keywords and prioritize job requirementsin 12 of 356, across 4 files
  • Stop and ask for clarification if required inputs are missingin 12 of 356, across 5 files
  • Map candidate experience to job requirementsin 11 of 356, across 3 files
  • Ask if the user wants adjustmentsin 11 of 356, across 3 files
  • Provide strengths and gap analysis after the resumein 10 of 356, across 2 files
  • Request candidate background details if not providedin 10 of 356, across 2 files
  • Format experience bullets as action verb plus resultin 10 of 356, across 2 files
  • Ask for missing inputs before startingin 10 of 356, across 9 files
  • Use exact job description terminologyin 9 of 356, across 1 file

Said here and by no other author read

  • extract keywords and role expectations
  • rewrite summary and experience sections
  • remove weak phrasing
  • check formatting and impact consistency
  • produce before and after summary

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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